Dynamic monitoring of land subsidence in mining area from multi-source remote-sensing data – a case study at Yanzhou, China

Abstract

Energy consumption in China is currently based on coal, but the exploitation of coal resources is accompanied by serious threats to the environment. In order to balance mine exploitation, land resource protection and land reclamation, there is an opportunity for monitoring land subsidence in mining area. This article examines a case study of Yanzhou mining area (YZMA) and proposes a new method for dynamic monitoring of land subsidence, which is a hybrid approach using a combination of multi-scale edge detection, relational model establishment and digital elevation model (DEM) difference analysis. A wavelet transform is used to extract the edges of water and marsh, which are buffered with the model to achieve the acquisition of the subsidence edge. DEM difference analysis is finally used to modify the results. The results indicate that this hybrid method improves subsidence monitoring performance by ±0.02 km2 of the area accuracy. This method can be viewed as an effective approach to monitor a wide range of land subsidence in plain mining areas of China.